How Savvy Companies Are Using Chinese AI

OpenAI’s November 2022 launch of ChatGPT caught Chinese technology companies completely off guard. Overnight, firms like Alibaba, Tencent, and Baidu, once competitive with global players like Google and Microsoft, had become laggards. But nearly three years later, Chinese companies have more than caught up to their U.S. rivals: They have forged a new parallel path with generative AI. DeepSeek, which was founded in 2023, is perhaps the most notable of the Chinese entrants in the AI space. In less than a year, and with a fraction of the computing and data resources of U.S. models, DeepSeek-R1 is performing comparably to OpenAI’s GPT-4o and Anthropic’s Claude 3.5 Sonnet. Another startup, 01.AI, has launched the Yi-Lightning model, which rocketed up the leaderboard in terms of price, performance, and accuracy. But what’s emerging in China isn’t a clone of Western systems. It’s a strategically distinct model of gen AI, adapted to thrive under different constraints and to meet different priorities. Firms such as DeepSeek are leveraging foundational advances while engineering distinct AI systems designed for cost-efficiency, rapid deployment, and targeted applications.

These developments are unfolding against the backdrop of mounting geopolitical pressures and export controls—particularly on semiconductor access—that were meant to cripple China’s gen AI development. Instead, they catalyzed it. Today more than 300 gen AI services are registered with the Cyberspace Administration of China. Huawei, for instance, fast-tracked the development of its Ascend chip series, building a homegrown alternative to Nvidia’s chips, and Ascend chips now power national-scale data centers.

Many global companies are integrating gen AI into their businesses, and most are using Western tools from companies like OpenAI, Google, and Anthropic. But they now find themselves navigating a second, very different ecosystem, one that has grown rapidly, quietly, and with a logic all its own. At the core of China’s momentum is the country’s commitment to building a modular and resilient AI infrastructure that enables rapid adaptation to local needs. Chinese firms are tackling challenges such as hallucinations, model costs (economic and environmental), and regulatory alignment with approaches that often diverge from those of the West. The ecosystem they’ve created is not only resilient but also highly efficient, and every layer of it, from AI chips to storage solutions, is attuned to local nuances. That approach differs sharply from the more generalized, broad-based research approach of the Western ecosystem.

The ongoing uncertainties surrounding U.S.–China tariffs further complicate the situation. Western technology, including large language models (LLMs) and infrastructure, is already hard to access in China. But now there is a possibility of restrictions on Chinese AI models in the United States, and the vetting of vendors will require more rigorous due diligence—from reviews of chip sourcing and cybersecurity audits to alignment with local regulations. Multinationals that operate in both regions must navigate a shifting landscape. Executives must weigh political risk, supply chain resilience, and governance compatibility alongside performance benchmarks when considering Chinese AI partners.

Western executives face a unique challenge. They can no longer assume that the best gen AI tools will all come from one ecosystem. Whether you’re deploying customer service platforms, logistics optimization tools, vertical applications in healthcare or finance, or general-purpose AI agents, you’ll most likely need to learn to work across Western and Chinese technology. Access to Chinese cloud providers, compliance with evolving AI governance, and compatibility with Chinese LLMs are fast becoming not just tech challenges but core business issues. Companies that fail to align their gen AI strategies with these new realities may find themselves outpaced by competitors who can move faster, for less money, and with better regulatory support. Navigating this terrain requires more than technical integration. It requires a strategic mindset.

China has built a parallel gen AI stack—one that works differently, moves quickly, and serves a different set of needs. By combining the best of China’s agile, deployment-ready models with the research strength and infrastructure of Western technology, companies can unlock new avenues for innovation and growth. This is not about choosing sides. It’s about being ready for a multipolar AI future. Now is the time to assess, partner, and integrate.

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